Towards Exascale Computing Architecture and Its Prototype: Services and Infrastructure

This paper presents the design and implementation of a scalable compute platform for processing large data sets in the scope of the EU H2020 project PROCESS. We are presenting requirements of the platform, related works, infrastructure with focus on the compute components and finally results of our work

Reference Exascale Architecture (Extended Version)

While political commitments for building exascale systems have been made, turning these systems into platforms for a wide range of exascale applications faces several technical, organisational and skills-related challenges. The key technical challenges are related to the availability of data. While the first exascale machines are likely to be built within a single site, the input data is in many cases impossible to store within a single site. Alongside handling of extreme-large amount of data, the exascale system has to process data from different sources, support accelerated computing, handle high volume of requests per day, minimize the size of data flows, and be extensible in terms of continuously increasing data as well as an increase in parallel requests being sent. These technical challenges are addressed by the general reference exascale architecture. It is divided into three main blocks: virtualization layer, distributed virtual file system, and manager of computing resources. Its main property is modularity which is achieved by containerization at two levels: 1) application containers - containerization of scientific workflows, 2) micro-infrastructure - containerization of extreme-large data service-oriented infrastructure. The paper also presents an instantiation of the reference architecture - the architecture of the PROCESS project (PROviding Computing solutions for ExaScale ChallengeS) and discusses its relation to the reference exascale architecture. The PROCESS architecture has been used as an exascale platform within various exascale pilot applications. This paper also presents performance modelling of exascale platform with its validation

Exascale computing and data architectures for brownfield applications

Despite the recent dramatic advances in the computational and data processing capacities of the commodity solutions, a numerous scientific, socioeconomic and industrial “grand challenges” exists that could be solved only through capabilities that exceed the current solutions by orders of magnitude. To demonstrate the feasibility of addressing these problems necessitating processing of exascale data sets, novel architectural approaches are needed. These architectures need to support efficient service composition and balancing infrastructure- and user-centric points of view of exascale infrastructures and services. This combination of bottom-up and top-down approaches aims at narrowing the gap between infrastructure services and paving the way towards future high capacity generations einfrastructure. The resulting architecture will help us provide computing solutions to exascale challenges within the H2020 project PROCESS